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    "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
    "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/geemap/tree/master/tutorials/Image/10_spectral_transformations.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
    "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/geemap/blob/master/tutorials/Image/10_spectral_transformations.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
    "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/geemap/blob/master/tutorials/Image/10_spectral_transformations.ipynb\"><img width=26px src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spectral transformations\n",
    "There are several spectral transformation methods in Earth Engine. These include instance methods on images such as `normalizedDifference()`, `unmix()`, `rgbToHsv()` and `hsvToRgb()`. The latter two methods are useful for pan sharpening. For example:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install Earth Engine API and geemap\n",
    "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://github.com/giswqs/geemap). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n",
    "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet.\n",
    "\n",
    "**Important note**: A key difference between folium and ipyleaflet is that ipyleaflet is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input, while folium is meant for displaying static data only ([source](https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a)). Note that [Google Colab](https://colab.research.google.com/) currently does not support ipyleaflet ([source](https://github.com/googlecolab/colabtools/issues/60#issuecomment-596225619)). Therefore, if you are using geemap with Google Colab, you should use [`import geemap.eefolium`](https://github.com/giswqs/geemap/blob/master/geemap/eefolium.py). If you are using geemap with [binder](https://mybinder.org/) or a local Jupyter notebook server, you can use [`import geemap`](https://github.com/giswqs/geemap/blob/master/geemap/geemap.py), which provides more functionalities for capturing user input (e.g., mouse-clicking and moving)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Installs geemap package\n",
    "import subprocess\n",
    "\n",
    "try:\n",
    "    import geemap\n",
    "except ImportError:\n",
    "    print('geemap package not installed. Installing ...')\n",
    "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])\n",
    "\n",
    "# Checks whether this notebook is running on Google Colab\n",
    "try:\n",
    "    import google.colab\n",
    "    import geemap.eefolium as emap\n",
    "except:\n",
    "    import geemap as emap\n",
    "\n",
    "# Authenticates and initializes Earth Engine\n",
    "import ee\n",
    "\n",
    "try:\n",
    "    ee.Initialize()\n",
    "except Exception as e:\n",
    "    ee.Authenticate()\n",
    "    ee.Initialize()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create an interactive map \n",
    "The default basemap is `Google Satellite`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/geemap.py#L13) can be added using the `Map.add_basemap()` function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = emap.Map(center=[40,-100], zoom=4)\n",
    "Map.add_basemap('ROADMAP') # Add Google Map\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add Earth Engine Python script "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load a Landsat 8 top-of-atmosphere reflectance image.\n",
    "image = ee.Image('LANDSAT/LC08/C01/T1_TOA/LC08_044034_20140318')\n",
    "Map.addLayer(\n",
    "    image,\n",
    "    {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 0.25, 'gamma': [1.1, 1.1, 1]},\n",
    "    'rgb')\n",
    "\n",
    "# Convert the RGB bands to the HSV color space.\n",
    "hsv = image.select(['B4', 'B3', 'B2']).rgbToHsv()\n",
    "\n",
    "# Swap in the panchromatic band and convert back to RGB.\n",
    "sharpened = ee.Image.cat([\n",
    "  hsv.select('hue'), hsv.select('saturation'), image.select('B8')\n",
    "]).hsvToRgb()\n",
    "\n",
    "# Display the pan-sharpened result.\n",
    "Map.setCenter(-122.44829, 37.76664, 13)\n",
    "Map.addLayer(sharpened,\n",
    "             {'min': 0, 'max': 0.25, 'gamma': [1.3, 1.3, 1.3]},\n",
    "             'pan-sharpened')\n",
    "\n",
    "Map.addLayerControl()\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Spectral unmixing is implemented in Earth Engine as the `image.unmix()` method. (For more flexible methods, see the [Array Transformations page](https://developers.google.com/earth-engine/arrays_transformations)). The following is an example of unmixing Landsat 5 with predetermined urban, vegetation and water endmembers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = emap.Map(center=[40, -100], zoom=4)\n",
    "\n",
    "bands = ['B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7']\n",
    "image = ee.Image('LANDSAT/LT05/C01/T1/LT05_044034_20080214') \\\n",
    "  .select(bands)\n",
    "Map.setCenter(-122.1899, 37.5010, 10) # San Francisco Bay\n",
    "Map.addLayer(image, {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 128}, 'image')\n",
    "\n",
    "# Define spectral endmembers.\n",
    "urban = [88, 42, 48, 38, 86, 115, 59]\n",
    "veg = [50, 21, 20, 35, 50, 110, 23]\n",
    "water = [51, 20, 14, 9, 7, 116, 4]\n",
    "\n",
    "# Unmix the image.\n",
    "fractions = image.unmix([urban, veg, water])\n",
    "Map.addLayer(fractions, {}, 'unmixed')\n",
    "# Map.setCenter(-122.44829, 37.76664, 13)\n",
    "\n",
    "Map.addLayerControl()\n",
    "Map"
   ]
  }
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